Browsing by Author "Bari, Salman"

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Citation - WoS: 7
Attitude Control of Quad-Copter Using Deterministic Policy Gradient Algorithms (dpga)
(Ieee, 2019) Ghouri, Usama Hamayun; Zafar, Muhammad Usama; Bari, Salman; Khan, Haroon; Khan, Muhammad Umer; Mechatronics Engineering; 15. Graduate School of Natural and Applied Sciences; 06. School Of Engineering; 01. Atılım University
In aerial robotics, intelligent control has been a buzz for the past few years. Extensive research efforts can be witnessed to produce control algorithms for stable flight operation of aerial robots using machine learning. Supervised learning has the tendency but training an agent using supervised learning can be a tedious task. Moreover, the data gathering could be expensive and always prone to inaccuracies due to parametric variations and system dynamics. An alternative approach is to ensure the stability of the aerial robots with the help of Deep Re-inforcement Learning (DRL). This paper deals with the intelligent control of quad-copter using deterministic policy gradient algorithms. In this research, state of the art Deep Deterministic Policy Gradient (DDPG) and Distributed Distributional Deep Deterministic Policy Gradient (D4PG) algorithms are employed for attitude control of quad-copter. An open source simulation environment GymFC is used for training of quad-copter. The results for comparative analysis of DDPG & D4PG algorithms are also presented, highlighting the attitude control performance.
Citation - WoS: 3
Sliding Mode Control for Autonomous Flight of Tethered Kite Under Varying Wind Speed Conditions
(Ieee, 2020) Bari, Salman; Khan, Muhammad Umer; Mechatronics Engineering; 15. Graduate School of Natural and Applied Sciences; 06. School Of Engineering; 01. Atılım University
High altitude wind is an energy-abundant source, representing the next generation of wind power technology. The power that can be extracted from wind grows cubically with wind speed, making higher altitudes a desirable choice to harvest wind energy. In this respect, large and fully-automated kites or planes can be used to capture such energy. Flight control is a key research area for using fully-automated kite power systems at utility scale. In this study, a novel control architecture is proposed for autonomous pattern 8 flight of tethered kites under varying wind speed conditions. The proposed scheme does not require a separate control system for turn maneuvers and straight flight path sections. Exponential reaching law-based Sliding Mode Control (SMC) and adaptive sliding mode control schemes are tested for flight control of a kite given a pre-specified trajectory. In this approach, the inversion of plant model is not required to address the problem of possible system instability, thus making the scheme proposed here more resilient towards system perturbations.